
# This Python 3 environment comes with many helpful analytics libraries installed
# It is defined by the kaggle/python Docker image: https://github.com/kaggle/docker-python
# For example, here's several helpful packages to load

import numpy as np # linear algebra
import pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)

# Input data files are available in the read-only "../input/" directory
# For example, running this (by clicking run or pressing Shift+Enter) will list all files under the input directory

import os
for dirname, _, filenames in os.walk('/kaggle/input'):
    for filename in filenames:
        print(os.path.join(dirname, filename))

# You can write up to 20GB to the current directory (/kaggle/working/) that gets preserved as output when you create a version using "Save & Run All" 
# You can also write temporary files to /kaggle/temp/, but they won't be saved outside of the current session

/kaggle/input/covid19-data-from-john-hopkins-university/CONVENIENT_global_deaths.csv
/kaggle/input/covid19-data-from-john-hopkins-university/RAW_global_deaths.csv
/kaggle/input/covid19-data-from-john-hopkins-university/RAW_global_confirmed_cases.csv
/kaggle/input/covid19-data-from-john-hopkins-university/CONVENIENT_us_deaths.csv
/kaggle/input/covid19-data-from-john-hopkins-university/CONVENIENT_global_metadata.csv
/kaggle/input/covid19-data-from-john-hopkins-university/RAW_us_confirmed_cases.csv
/kaggle/input/covid19-data-from-john-hopkins-university/CONVENIENT_us_confirmed_cases.csv
/kaggle/input/covid19-data-from-john-hopkins-university/CONVENIENT_global_confirmed_cases.csv
/kaggle/input/covid19-data-from-john-hopkins-university/CONVENIENT_us_metadata.csv
/kaggle/input/covid19-data-from-john-hopkins-university/RAW_us_deaths.csv


# import package
import matplotlib.pyplot as plt
import seaborn as sns 
import statsmodels as sm
import folium as fl
#import vincent 
from pathlib import Path
from sklearn.impute import SimpleImputer
import geopandas as gpd
import mapclassify as mpc
import warnings
import plotly.offline as py
import plotly.express as px
import cufflinks as cf


%matplotlib inline
pd.options.plotting.backend
#pd.plotting.register_matplotlib_converters()
gpd.plotting.plot_linestring_collection
py.init_notebook_mode(connected=False)
cf.set_config_file(offline=True)
sns.set()
warnings.filterwarnings('ignore')


raw_conf = pd.read_csv('/kaggle/input/covid19-data-from-john-hopkins-university/RAW_global_confirmed_cases.csv')
raw_deaths = pd.read_csv('/kaggle/input/covid19-data-from-john-hopkins-university/RAW_global_deaths.csv')
conv_conf = pd.read_csv('/kaggle/input/covid19-data-from-john-hopkins-university/CONVENIENT_global_confirmed_cases.csv')
conv_deaths = pd.read_csv('/kaggle/input/covid19-data-from-john-hopkins-university/CONVENIENT_global_deaths.csv')
meta_conf = pd.read_csv('/kaggle/input/covid19-data-from-john-hopkins-university/CONVENIENT_global_metadata.csv')


raw_conf.head()


raw_deaths.tail()


raw_conf.info()

<class 'pandas.core.frame.DataFrame'>
RangeIndex: 271 entries, 0 to 270
Columns: 348 entries, Country/Region to 12/30/20
dtypes: float64(2), int64(344), object(2)
memory usage: 736.9+ KB


raw_deaths.info()

<class 'pandas.core.frame.DataFrame'>
RangeIndex: 271 entries, 0 to 270
Columns: 348 entries, Country/Region to 12/30/20
dtypes: float64(2), int64(344), object(2)
memory usage: 736.9+ KB


conv_conf.tail()


conv_conf.info()

<class 'pandas.core.frame.DataFrame'>
RangeIndex: 344 entries, 0 to 343
Columns: 272 entries, Country/Region to Zimbabwe
dtypes: float64(188), object(84)
memory usage: 731.1+ KB


#confirmed case descriptive 
raw_conf.iloc[:, -1].describe()

count    2.710000e+02
mean     3.051955e+05
std      1.473547e+06
min      0.000000e+00
25%      7.385000e+02
50%      8.972000e+03
75%      1.262875e+05
max      1.974047e+07
Name: 12/30/20, dtype: float64


#deaths case descriptive
raw_deaths.iloc[:, -1].describe()

count       271.000000
mean       6660.523985
std       28270.199908
min           0.000000
25%           6.000000
50%         124.000000
75%        1991.500000
max      342312.000000
Name: 12/30/20, dtype: float64


date = list(raw_conf.columns)[-1]# last date
country_confirmed = raw_conf.groupby('Country/Region')[date].agg('sum').reset_index()


#top 10 country most affected by covid 19
country_confirmed.sort_values(by=date, ascending=False).style.background_gradient('viridis')


country_deaths = raw_deaths.groupby('Country/Region')[date].agg('sum').reset_index()


#top 10 country most killed by covid 19
country_deaths.sort_values(by=date, ascending=False).style.background_gradient('viridis')


plt.figure(figsize=(15,5))
sns.distplot(country_confirmed[date], bins=10)
plt.title(f'Covid19 confirmed case distribution for date {date}')
plt.show()


plt.figure(figsize=(15,5))
sns.distplot(country_deaths[date], bins=10)
plt.title(f'Covid19 deaths case distribution for date {date}')
plt.show()


sns.jointplot(x=raw_conf.Long, y=raw_conf. Lat, kind='hex')
plt.show()


confirmed = raw_conf.groupby('Country/Region')[list(raw_conf.columns)[4:]].agg('sum')


death = raw_deaths.groupby('Country/Region')[list(raw_conf.columns)[4:]].agg('sum')


case_conf = confirmed.T


case_conf[['US', 'India', 'Brazil', 'Russia','France','Germany']].iplot(title='6 countries having huge COVID-19 confirmed cases in the world.',
                                                             legend=True)


fatalities = death.T


fatalities[['US', 'India', 'Brazil', 'Mexico','Italy','Germany']].iplot(title='6 countries having huge COVID-19 deaths in the world.',
                                                            legend=True)


region = []
cases = []
time = []
latitude = []
longitude = []
fat = []
for u in list(raw_conf.columns)[4:]:
    time.append([u for i in range(raw_conf.shape[0])])
    region.append(list(raw_conf['Country/Region']))
    cases.append(list(raw_conf[u]))
    
    latitude.append(list(raw_conf.Lat))
    longitude.append(list(raw_conf.Long))
    fat.append(list(raw_deaths[u]))


global_covid19 = pd.DataFrame()


global_covid19['date'] = np.concatenate(time)
global_covid19['country'] = np.concatenate(region)
global_covid19['Lat'] = np.concatenate(latitude)
global_covid19['Long'] = np.concatenate(longitude)
global_covid19['cases'] = np.concatenate(cases)
global_covid19['fatalities'] = np.concatenate(fat)


global_covid19.head()


center_point = dict(lon=0, lat=0)
figx = px.density_mapbox(global_covid19, lat='Lat', lon='Long', z="cases",
                        center = center_point, hover_name='country', zoom = 5,
                         range_color= [20, 20] , radius=20,
                        mapbox_style= 'open-street-map', title='Novel COVID-19 cases in the world',
                        animation_frame='date')
figx.update(layout_coloraxis_showscale=True)
figx.show()


center = dict(lon=0, lat=0)
figy = px.density_mapbox(global_covid19, lat='Lat', lon='Long', z="fatalities",
                        center = center, hover_name='country', zoom = 5,
                         range_color= [20, 20] , radius=20,
                        mapbox_style= 'open-street-map', title='Novel COVID-19 fatalities in the world.',
                        animation_frame='date')
figy.update(layout_coloraxis_showscale=True)
figy.show()


replace = ['Dem. Rep. Congo',  'Congo','Central African Rep.',
          'Eq. Guinea','eSwatini','Bosnia and Herz.', 'S. Sudan', 'Dominican Rep.', 
          'United States of America', 'South Korea', "Côte d'Ivoire"]

name = ['Congo (Kinshasa)',  'Congo (Brazzaville)', 
        'Central African Republic', 'Equatorial Guinea', 'Eswatini', 'Bosnia and Herzegovina', 'South Sudan',
       'Dominica','US', 'Korea, South',"Côte d'Ivoire"]


global_covid19 = global_covid19.replace(to_replace=name, value=replace)


end_date = global_covid19.date.unique()[-1] #today
yesterday = global_covid19.date.unique()[-2] #yesterday


geoCovid = gpd.GeoDataFrame(global_covid19, geometry=gpd.points_from_xy(global_covid19.Long, global_covid19.Lat))


geoCovid.crs = 'epsg:4326'


geoCovid.head()


world_path_file = gpd.datasets.get_path('naturalearth_lowres') # upload natural data map
world = gpd.read_file(world_path_file)


need_data = global_covid19[global_covid19.date == end_date]
before_data = global_covid19[global_covid19.date == yesterday]


before_data.head()


need_data['new_cases'] = need_data['cases'].values - before_data['cases'].values
need_data['new_fatalities'] = need_data['fatalities'].values - before_data['fatalities'].values


need_data.head()


need_dat = need_data.groupby('country')[['cases', 'fatalities','new_cases', 'new_fatalities']].agg('sum').reset_index()


geo_merged = world.merge(need_dat[['country','cases','fatalities', 'new_cases', 'new_fatalities']] , 
                         left_on='name', right_on='country')


geo_merged.tail()


geo_merged['prevalence'] = (geo_merged.cases/geo_merged.pop_est)*100000
geo_merged['incidence'] = (geo_merged.new_cases/geo_merged.pop_est)*100000
geo_merged['lethality'] = (geo_merged.fatalities/geo_merged.cases)*100


geo_merged.tail()


geo_merged.plot(cmap='cividis_r', column='cases', legend=True, figsize=(15,9), scheme='quantiles', k=4)
plt.title(f'SARS-Cov 2 cases in the worldwide for date {end_date}.')
plt.show()


geo_merged.plot(cmap='OrRd', column='fatalities', legend=True, figsize=(15,9), scheme='quantiles', k=3)
plt.title(f'SARS-Cov 2 fatalities in the worldwide for date {end_date}.')
plt.show()


most_aff_country = need_data[need_data.country.isin(['United States of America', 'Brazil', 'India', 'France',
                                                    'Russia', 'United Kingdom', 'Turkey', 'Italy', 'Spain',
                                                    'Argentina', 'Colombia', 'Germany','Mexico', 'Poland',
                                                    'Iran', 'Peru', 'Ukraine', 'South Africa', 'Netherlands',
                                                    'Indonesia'])]


ax = world.plot(figsize=(20,20), edgecolor='black', linestyle=':', color='whitesmoke')
ax.scatter(most_aff_country.Long, most_aff_country.Lat, cmap='cividis', s=most_aff_country.cases/10000,
          c=most_aff_country.cases )
for id in [10, 100, 150, 200]:
    plt.scatter([], [], c='k', alpha=0.5, s=id, label = str(id))
plt.legend(scatterpoints=1, frameon=True, labelspacing=1, title='Confirmed size')
plt.title('The spreading of COVID-19 cases in the 20 countries most affected ')
plt.show()


sars_bilan = []


for u in list(geo_merged.continent.unique()):
    x = geo_merged[geo_merged.continent == u]
    c = x.groupby('continent')[['cases', 'fatalities']].agg('sum')
    sars_bilan.append(c)


pd.concat(sars_bilan)['cases'].iplot(title='SARS-Cov 2 cases in the Earth planet', legend=True, logy=False, kind='bar')


pd.concat(sars_bilan)['fatalities'].iplot(title='SARS-Cov 2 fatalities in the Earth planet', legend=True, logy=False, kind='bar')


geo_merged[['country', 'prevalence']].sort_values(by='prevalence', ascending=False).style.background_gradient('viridis')


geo_merged[['country', 'prevalence']].sort_values(by='prevalence', ascending=False).style.background_gradient('viridis')


geo_merged[['country', 'incidence']].sort_values(by='incidence', ascending=False).style.background_gradient('viridis')


geo_merged.plot(cmap='rainbow', column='incidence', legend=True, figsize=(15,9), scheme='quantiles', k=3)
plt.title(f'SARS-Cov 2 incidence per 100000 inhabitants in the worldwide for date {end_date}.')
plt.show()


geo_merged[['country', 'new_cases']].sort_values(by='new_cases', ascending=False).style.background_gradient('viridis')


geo_merged.plot(cmap='rainbow', column='new_cases', legend=True, figsize=(15,9), scheme='quantiles', k=3)
plt.title(f'SARS-Cov 2 new cases in the worldwide for date {end_date}.')
plt.show()


geo_merged[['country', 'new_fatalities']].sort_values(by='new_fatalities', ascending=False).style.background_gradient('viridis')


geo_merged.plot(cmap='OrRd', column='new_fatalities', legend=True, figsize=(15,9), scheme='quantiles', k=2)
plt.title(f'SARS-Cov 2 new fatalities in the worldwide for date {end_date}.')
plt.show()


geo_merged[['country', 'lethality']].sort_values(by='lethality', ascending=False).style.background_gradient('viridis')


geo_merged.plot(cmap='OrRd', column='lethality', legend=True, figsize=(15,9), scheme='quantiles', k=3)
plt.title(f'SARS-Cov 2 lethality in the worldwide for date {end_date}.')
plt.show()

	Country/Region	Province/State	Lat	Long	...	12/21/20	12/22/20	12/23/20	12/24/20	12/25/20	12/26/20	12/27/20	12/28/20	12/29/20	12/30/20
0	Afghanistan	NaN	33.93911	67.709953	...	50013	50190	50433	50655	50810	50886	51039	51280	51350	51405
1	Albania	NaN	41.15330	20.168300	...	53425	53814	54317	54827	55380	55755	56254	56572	57146	57727
2	Algeria	NaN	28.03390	1.659600	...	95659	96069	96549	97007	97441	97857	98249	98631	98988	99311
3	Andorra	NaN	42.50630	1.521800	...	7602	7633	7669	7699	7756	7806	7821	7875	7919	7983
4	Angola	NaN	-11.20270	17.873900	...	16686	16802	16931	17029	17099	17149	17240	17296	17371	17433

	Country/Region	Province/State	Lat	Long	...	12/21/20	12/22/20	12/23/20	12/24/20	12/25/20	12/26/20	12/27/20	12/28/20	12/29/20	12/30/20
266	Vietnam	NaN	14.058324	108.277199	...	35	35	35	35	35	35	35	35	35	35
267	West Bank and Gaza	NaN	31.952200	35.233200	...	1169	1198	1226	1243	1260	1281	1309	1332	1351	1371
268	Yemen	NaN	15.552727	48.516388	...	606	606	606	606	606	606	607	607	610	610
269	Zambia	NaN	-13.133897	27.849332	...	375	379	380	381	381	382	383	384	385	386
270	Zimbabwe	NaN	-19.015438	29.154857	...	322	326	330	339	341	341	349	354	359	360

	Country/Region	Afghanistan	Albania	Algeria	Andorra	Angola	Antigua and Barbuda	Argentina	Armenia	...	United Kingdom.10	Uruguay	Uzbekistan	Venezuela	Vietnam	West Bank and Gaza	Yemen	Zambia	Zimbabwe
339	12/26/20	76.0	375.0	416.0	50.0	50.0	0.0	3713.0	586.0	...	34693.0	370.0	98.0	348.0	1.0	1306.0	0.0	100.0	83.0
340	12/27/20	153.0	499.0	392.0	15.0	91.0	0.0	5030.0	485.0	...	32340.0	510.0	85.0	365.0	1.0	1189.0	2.0	163.0	114.0
341	12/28/20	241.0	318.0	382.0	54.0	56.0	3.0	7216.0	114.0	...	41385.0	578.0	81.0	320.0	10.0	1217.0	2.0	109.0	71.0
342	12/29/20	70.0	574.0	357.0	44.0	75.0	0.0	11650.0	348.0	...	53135.0	656.0	75.0	225.0	3.0	1149.0	0.0	234.0	177.0
343	12/30/20	55.0	581.0	323.0	64.0	62.0	0.0	11765.0	582.0	...	50023.0	518.0	78.0	260.0	2.0	1277.0	1.0	285.0	300.0

	Country/Region	12/30/20
177	US	19740468
79	India	10266674
23	Brazil	7619200
141	Russia	3100018
62	France	2657624
181	United Kingdom	2440202
176	Turkey	2194272
85	Italy	2083689
161	Spain	1910218
66	Germany	1741153
37	Colombia	1626461
6	Argentina	1613928
114	Mexico	1413935
137	Poland	1281414
81	Iran	1218753
179	Ukraine	1076880
159	South Africa	1039161
135	Peru	1010496
123	Netherlands	798592
80	Indonesia	735124
46	Czechia	701622
16	Belgium	644242
140	Romania	627941
35	Chile	606950
82	Iraq	594442
32	Canada	577266
13	Bangladesh	512496
131	Pakistan	479715
136	Philippines	472532
166	Switzerland	447905
165	Sweden	437379
119	Morocco	437332
84	Israel	416584
138	Portugal	406051
149	Saudi Arabia	362601
9	Austria	357902
151	Serbia	334991
77	Hungary	319543
88	Jordan	293067
122	Nepal	260059
132	Panama	242744
87	Japan	231271
65	Georgia	225893
10	Azerbaijan	217636
52	Ecuador	211512
43	Croatia	208446
180	United Arab Emirates	206092
25	Bulgaria	201220
89	Kazakhstan	200443
15	Belarus	192361
97	Lebanon	177996
155	Slovakia	173228
51	Dominican Republic	169579
41	Costa Rica	168114
47	Denmark	161862
7	Armenia	158878
20	Bolivia	158372
93	Kuwait	150298
115	Moldova	143841
139	Qatar	143621
102	Lithuania	138219
68	Greece	137918
175	Tunisia	137216
70	Guatemala	137166
187	West Bank and Gaza	136736
53	Egypt	136644
130	Oman	128719
59	Ethiopia	123856
27	Burma	123740
76	Honduras	120912
156	Slovenia	119740
185	Venezuela	113121
21	Bosnia and Herzegovina	110985
107	Malaysia	110485
134	Paraguay	106958
100	Libya	99935
2	Algeria	99311
90	Kenya	96251
36	China	95876
12	Bahrain	92425
83	Ireland	90157
127	Nigeria	86576
128	North Macedonia	82794
94	Kyrgyzstan	80843
183	Uzbekistan	76985
91	Korea, South	60740
154	Singapore	58569
1	Albania	57727
67	Ghana	54771
0	Afghanistan	51405
92	Kosovo	50910
129	Norway	49010
118	Montenegro	47782
103	Luxembourg	46415
54	El Salvador	45960
162	Sri Lanka	42702
96	Latvia	39043
61	Finland	35858
178	Uganda	34677
8	Australia	28405
57	Estonia	27256
31	Cameroon	26277
121	Namibia	23333
163	Sudan	23316
42	Cote d'Ivoire	22366
45	Cyprus	22019
189	Zambia	20462
150	Senegal	18945
120	Mozambique	18485
182	Uruguay	18480
105	Madagascar	17714
4	Angola	17433
40	Congo (Kinshasa)	17376
22	Botswana	14700
112	Mauritania	14191
108	Maldives	13738
71	Guinea	13707
190	Zimbabwe	13625
169	Tajikistan	13296
86	Jamaica	12793
110	Malta	12665
29	Cabo Verde	11793
44	Cuba	11687
167	Syria	11344
17	Belize	10724
74	Haiti	9999
63	Gabon	9571
58	Eswatini	9146
142	Rwanda	8250
3	Andorra	7983
11	Bahamas	7857
174	Trinidad and Tobago	7132
109	Mali	7029
39	Congo (Brazzaville)	6908
171	Thailand	6690
26	Burkina Faso	6631
106	Malawi	6471
73	Guyana	6319
164	Suriname	6181
125	Nicaragua	6046
49	Djibouti	5824
78	Iceland	5754
55	Equatorial Guinea	5264
33	Central African Republic	4963
158	Somalia	4714
64	Gambia	3797
173	Togo	3611
160	South Sudan	3540
18	Benin	3251
126	Niger	3208
98	Lesotho	3094
153	Sierra Leone	2583
72	Guinea-Bissau	2452
147	San Marino	2384
124	New Zealand	2162
101	Liechtenstein	2104
188	Yemen	2097
34	Chad	2077
99	Liberia	1779
186	Vietnam	1456
56	Eritrea	1252
117	Mongolia	1215
148	Sao Tome and Principe	1014
116	Monaco	853
28	Burundi	809
168	Taiwan*	797
133	Papua New Guinea	780
38	Comoros	765
48	Diamond Princess	712
19	Bhutan	655
113	Mauritius	527
170	Tanzania	509
14	Barbados	372
30	Cambodia	366
144	Saint Lucia	340
152	Seychelles	256
5	Antigua and Barbuda	158
24	Brunei	157
69	Grenada	127
145	Saint Vincent and the Grenadines	115
50	Dominica	88
60	Fiji	49
172	Timor-Leste	44
95	Laos	41
143	Saint Kitts and Nevis	32
75	Holy See	27
157	Solomon Islands	17
104	MS Zaandam	9
111	Marshall Islands	4
146	Samoa	2
184	Vanuatu	1

	Country/Region	12/30/20
177	US	342312
23	Brazil	193875
79	India	148738
114	Mexico	124897
85	Italy	73604
181	United Kingdom	72657
62	France	64508
141	Russia	55692
81	Iran	55095
161	Spain	50689
6	Argentina	43163
37	Colombia	42909
135	Peru	37574
66	Germany	33230
159	South Africa	28033
137	Poland	28019
80	Indonesia	21944
176	Turkey	20642
16	Belgium	19441
179	Ukraine	19058
35	Chile	16499
140	Romania	15596
32	Canada	15498
52	Ecuador	14023
82	Iraq	12808
46	Czechia	11429
123	Netherlands	11417
131	Pakistan	10105
77	Hungary	9429
136	Philippines	9230
20	Bolivia	9149
165	Sweden	8727
166	Switzerland	7594
53	Egypt	7576
13	Bangladesh	7531
25	Bulgaria	7515
119	Morocco	7355
138	Portugal	6830
149	Saudi Arabia	6214
9	Austria	6149
70	Guatemala	4803
68	Greece	4788
36	China	4781
175	Tunisia	4620
21	Bosnia and Herzegovina	4050
132	Panama	3975
43	Croatia	3860
88	Jordan	3815
84	Israel	3307
87	Japan	3243
151	Serbia	3163
76	Honduras	3111
115	Moldova	2960
7	Armenia	2807
89	Kazakhstan	2761
2	Algeria	2751
156	Slovenia	2665
27	Burma	2664
10	Azerbaijan	2609
128	North Macedonia	2488
65	Georgia	2481
51	Dominican Republic	2409
134	Paraguay	2242
83	Ireland	2226
0	Afghanistan	2181
41	Costa Rica	2171
155	Slovakia	2065
59	Ethiopia	1918
122	Nepal	1847
90	Kenya	1667
130	Oman	1497
163	Sudan	1468
100	Libya	1459
97	Lebanon	1456
102	Lithuania	1422
15	Belarus	1414
187	West Bank and Gaza	1371
94	Kyrgyzstan	1354
54	El Salvador	1327
92	Kosovo	1325
127	Nigeria	1278
47	Denmark	1256
1	Albania	1174
185	Venezuela	1025
93	Kuwait	933
8	Australia	909
91	Korea, South	900
167	Syria	704
118	Montenegro	681
180	United Arab Emirates	665
96	Latvia	626
183	Uzbekistan	614
188	Yemen	610
40	Congo (Kinshasa)	584
61	Finland	556
103	Luxembourg	495
107	Malaysia	463
31	Cameroon	448
129	Norway	436
4	Angola	405
150	Senegal	402
189	Zambia	386
190	Zimbabwe	360
12	Bahrain	352
112	Mauritania	339
67	Ghana	335
86	Jamaica	302
109	Mali	269
105	Madagascar	261
178	Uganda	251
139	Qatar	245
17	Belize	242
74	Haiti	236
57	Estonia	226
110	Malta	216
162	Sri Lanka	199
121	Namibia	196
106	Malawi	189
58	Eswatini	184
182	Uruguay	174
11	Bahamas	170
120	Mozambique	165
125	Nicaragua	165
73	Guyana	164
44	Cuba	145
42	Cote d'Ivoire	137
158	Somalia	130
174	Trinidad and Tobago	126
64	Gambia	124
164	Suriname	121
45	Cyprus	119
29	Cabo Verde	112
39	Congo (Brazzaville)	107
34	Chad	104
126	Niger	102
169	Tajikistan	90
55	Equatorial Guinea	86
142	Rwanda	86
26	Burkina Faso	84
3	Andorra	84
99	Liberia	83
71	Guinea	80
153	Sierra Leone	76
173	Togo	68
63	Gabon	64
160	South Sudan	63
33	Central African Republic	63
171	Thailand	61
49	Djibouti	61
147	San Marino	59
98	Lesotho	51
108	Maldives	48
72	Guinea-Bissau	45
18	Benin	44
22	Botswana	40
101	Liechtenstein	39
186	Vietnam	35
154	Singapore	29
78	Iceland	29
124	New Zealand	25
170	Tanzania	21
148	Sao Tome and Principe	17
48	Diamond Princess	13
113	Mauritius	10
133	Papua New Guinea	9
38	Comoros	9
168	Taiwan*	7
14	Barbados	7
5	Antigua and Barbuda	5
144	Saint Lucia	5
116	Monaco	3
24	Brunei	3
28	Burundi	2
104	MS Zaandam	2
60	Fiji	2
117	Mongolia	1
56	Eritrea	1
69	Grenada	0
157	Solomon Islands	0
19	Bhutan	0
75	Holy See	0
172	Timor-Leste	0
50	Dominica	0
143	Saint Kitts and Nevis	0
184	Vanuatu	0
30	Cambodia	0
145	Saint Vincent and the Grenadines	0
146	Samoa	0
152	Seychelles	0
111	Marshall Islands	0
95	Laos	0

I. Data preprocessing¶

II.Exploratory data analysis¶

2.1 Descriptive Analysis¶

2.2 Visualisation¶

Geo-spatial Analysis¶

COVID-19 Worldwide Spread¶

Prevalence¶

Incidence¶

New fatalities¶

Case fatality rate¶

	date	country	Lat	Long	cases	fatalities	geometry
92682	12/29/20	Afghanistan	33.93911	67.709953	51350	2179	POINT (67.70995 33.93911)
92683	12/29/20	Albania	41.15330	20.168300	57146	1170	POINT (20.16830 41.15330)
92684	12/29/20	Algeria	28.03390	1.659600	98988	2745	POINT (1.65960 28.03390)
92685	12/29/20	Andorra	42.50630	1.521800	7919	84	POINT (1.52180 42.50630)
92686	12/29/20	Angola	-11.20270	17.873900	17371	403	POINT (17.87390 -11.20270)

	date	country	Lat	Long	cases	fatalities	geometry	new_cases	new_fatalities
92953	12/30/20	Afghanistan	33.93911	67.709953	51405	2181	POINT (67.70995 33.93911)	55	2
92954	12/30/20	Albania	41.15330	20.168300	57727	1174	POINT (20.16830 41.15330)	581	4
92955	12/30/20	Algeria	28.03390	1.659600	99311	2751	POINT (1.65960 28.03390)	323	6
92956	12/30/20	Andorra	42.50630	1.521800	7983	84	POINT (1.52180 42.50630)	64	0
92957	12/30/20	Angola	-11.20270	17.873900	17433	405	POINT (17.87390 -11.20270)	62	2

	pop_est	continent	name	iso_a3	gdp_md_est	geometry	country	cases	fatalities	new_cases	new_fatalities
155	7111024	Europe	Serbia	SRB	101800.0	POLYGON ((18.82982 45.90887, 18.82984 45.90888...	Serbia	334991	3163	3236	44
156	642550	Europe	Montenegro	MNE	10610.0	POLYGON ((20.07070 42.58863, 19.80161 42.50009...	Montenegro	47782	681	378	4
157	1895250	Europe	Kosovo	-99	18490.0	POLYGON ((20.59025 41.85541, 20.52295 42.21787...	Kosovo	50910	1325	0	0
158	1218208	North America	Trinidad and Tobago	TTO	43570.0	POLYGON ((-61.68000 10.76000, -61.10500 10.890...	Trinidad and Tobago	7132	126	5	1
159	13026129	Africa	S. Sudan	SSD	20880.0	POLYGON ((30.83385 3.50917, 29.95350 4.17370, ...	S. Sudan	3540	63	29	0

	country	prevalence
118	Luxembourg	7812.263309
156	Montenegro	7436.308458
140	Czechia	6572.741981
29	Panama	6467.754218
78	Qatar	6205.788601
137	Slovenia	6071.620170
3	United States of America	6043.756661
119	Belgium	5606.323228
117	Switzerland	5438.180213
79	Kuwait	5226.989291
99	Armenia	5217.341047
70	Israel	5019.262128
108	Lithuania	4894.684898
116	Croatia	4856.509467
155	Serbia	4710.868646
120	Netherlands	4674.305735
133	Georgia	4585.421602
100	Sweden	4391.140714
106	Moldova	4140.356654
104	Austria	4088.246693
39	France	3960.327875
122	Spain	3901.735766
130	United Kingdom	3767.519910
81	Oman	3758.892835
121	Portugal	3746.025883
25	Brazil	3674.499830
8	Argentina	3643.729989
9	Chile	3411.888753
28	Colombia	3409.877002
30	Costa Rica	3409.841838
77	United Arab Emirates	3393.871527
128	Italy	3353.335543
103	Poland	3330.400876
27	Peru	3255.814673
105	Hungary	3243.813094
139	Slovakia	3180.929846
35	Belize	2976.028595
107	Romania	2916.590629
129	Denmark	2887.326104
154	Bosnia and Herz.	2878.106603
76	Jordan	2859.728989
71	Lebanon	2857.173126
112	Bulgaria	2833.481893
114	Turkey	2714.164345
157	Kosovo	2686.189157
102	Ukraine	2445.571789
18	Bahamas	2380.995673
132	Azerbaijan	2184.794179
17	Russia	2179.159331
110	Estonia	2177.725613
111	Germany	2160.399822
101	Belarus	2014.304672
109	Latvia	2007.720697
21	South Africa	1894.842436
115	Albania	1893.938524
146	Cyprus	1802.547421
123	Ireland	1799.145178
131	Iceland	1693.613189
2	Canada	1620.455832
143	Paraguay	1540.351675
80	Iraq	1516.738917
149	Libya	1502.056902
97	Iran	1485.893393
26	Bolivia	1421.877113
96	Kyrgyzstan	1396.463920
32	Honduras	1337.708426
40	Ecuador	1298.343438
147	Morocco	1286.775648
113	Greece	1280.756787
145	Saudi Arabia	1269.088334
74	Tunisia	1203.248040
23	Mexico	1135.008892
4	Kazakhstan	1080.165232
38	Suriname	1044.230714
45	Namibia	939.036856
19	Norway	921.232809
34	Guatemala	887.189559
92	Nepal	885.027129
37	Guyana	856.560366
89	India	800.872642
33	El Salvador	744.651946
63	Eq. Guinea	676.295484
151	Djibouti	673.087036
44	Botswana	663.699434
138	Finland	653.006309
67	eSwatini	623.384625
158	Trinidad and Tobago	585.450104
24	Uruguay	549.975775
62	Gabon	540.046438
134	Philippines	453.241689
41	Jamaica	427.779270
48	Mauritania	377.563707
36	Venezuela	361.362580
135	Malaysia	352.064968
90	Bangladesh	324.720973
7	Indonesia	282.109876
5	Uzbekistan	258.783034
75	Algeria	242.402612
93	Pakistan	234.093120
12	Kenya	202.141145
54	Ghana	199.167823
126	Sri Lanka	190.554126
73	Gambia	185.096446
142	Japan	182.893193
22	Lesotho	158.014997
95	Tajikistan	157.004353
94	Afghanistan	150.638197
148	Egypt	140.810481
61	Congo	139.423906
56	Guinea-Bissau	136.804554
46	Senegal	129.154117
64	Zambia	128.111695
125	Australia	122.264528
87	South Korea	118.676159
150	Ethiopia	117.566186
55	Guinea	110.416843
52	Cameroon	105.129509
42	Cuba	104.840525
31	Nicaragua	100.332711
43	Zimbabwe	98.695524
15	Haiti	93.916301
60	Central African Rep.	88.229260
152	Uganda	87.634295
91	Bhutan	86.378790
72	Madagascar	70.702827
66	Mozambique	69.561242
153	Rwanda	69.319087
98	Syria	62.922424
11	Somalia	62.591401
13	Sudan	62.432498
68	Angola	59.477440
124	New Zealand	47.934440
51	Nigeria	45.415188
53	Togo	45.335531
58	Sierra Leone	41.910081
88	Mongolia	39.599210
47	Mali	39.300552
57	Liberia	37.939689
136	Brunei	35.392804
65	Malawi	33.709716
59	Burkina Faso	32.977730
49	Benin	29.450652
159	S. Sudan	27.176147
141	Eritrea	21.152511
10	Dem. Rep. Congo	20.859256
14	Chad	17.199425
50	Niger	16.668967
6	Papua New Guinea	11.288477
84	Thailand	9.778681
144	Yemen	7.479448
69	Burundi	7.055178
127	China	6.951048
0	Fiji	5.320662
20	Timor-Leste	3.407266
83	Cambodia	2.258634
86	Vietnam	1.514141
1	Tanzania	0.943450
16	Dominican Rep.	0.819806
85	Laos	0.575301
82	Vanuatu	0.353589

	country	incidence
140	Czechia	153.821322
108	Lithuania	139.312905
137	Slovenia	123.470813
29	Panama	118.966988
100	Sweden	88.810919
110	Estonia	77.741672
130	United Kingdom	77.565887
109	Latvia	70.295679
3	United States of America	70.123673
117	Switzerland	65.854789
111	Germany	60.853152
156	Montenegro	58.828107
146	Cyprus	57.631745
139	Slovakia	55.840901
121	Portugal	55.805085
120	Netherlands	55.798401
118	Luxembourg	55.038460
70	Israel	50.435521
129	Denmark	49.732891
71	Lebanon	46.197354
155	Serbia	45.506807
116	Croatia	43.102494
39	France	39.510530
133	Georgia	35.279813
123	Ireland	34.283876
122	Spain	34.143441
103	Poland	33.215279
21	South Africa	32.293032
44	Botswana	30.475994
104	Austria	29.128167
106	Moldova	28.496417
77	United Arab Emirates	28.373933
25	Brazil	26.837757
30	Costa Rica	26.672032
8	Argentina	26.561583
128	Italy	26.074305
119	Belgium	24.635930
28	Colombia	24.401174
112	Bulgaria	24.346935
2	Canada	23.745441
107	Romania	22.642859
74	Tunisia	21.168382
101	Belarus	20.492689
105	Hungary	20.018587
114	Turkey	19.409930
45	Namibia	19.398096
99	Armenia	19.112102
102	Ukraine	19.085307
115	Albania	19.061761
17	Russia	18.343494
9	Chile	16.661732
76	Jordan	16.334785
35	Belize	15.540619
24	Uruguay	15.415988
67	eSwatini	14.449764
38	Suriname	14.022189
154	Bosnia and Herz.	13.770101
19	Norway	13.759282
26	Bolivia	13.332455
143	Paraguay	11.838003
132	Azerbaijan	10.560769
23	Mexico	9.958676
33	El Salvador	8.830185
149	Libya	8.792748
113	Greece	8.747755
78	Qatar	8.339429
138	Finland	7.976372
97	Iran	7.646770
40	Ecuador	7.280132
79	Kuwait	7.129388
147	Morocco	6.305416
135	Malaysia	5.958831
34	Guatemala	5.685371
48	Mauritania	5.374383
131	Iceland	5.298060
27	Peru	5.116531
4	Kazakhstan	4.785334
22	Lesotho	4.545357
62	Gabon	3.441943
18	Bahamas	3.333455
96	Kyrgyzstan	3.264744
7	Indonesia	3.070833
142	Japan	3.049393
126	Sri Lanka	2.882721
81	Oman	2.511399
91	Bhutan	2.505644
37	Guyana	2.439957
80	Iraq	2.298932
43	Zimbabwe	2.173112
63	Eq. Guinea	2.055609
87	South Korea	1.889362
64	Zambia	1.784373
92	Nepal	1.739024
89	India	1.702269
148	Egypt	1.454024
41	Jamaica	1.370980
47	Mali	1.302750
151	Djibouti	1.271284
93	Pakistan	1.207760
136	Brunei	1.127159
153	Rwanda	1.025082
152	Uganda	1.000755
134	Philippines	0.964932
46	Senegal	0.947607
36	Venezuela	0.830564
75	Algeria	0.788392
90	Bangladesh	0.782504
42	Cuba	0.771480
88	Mongolia	0.651839
98	Syria	0.560223
141	Eritrea	0.540639
51	Nigeria	0.532963
59	Burkina Faso	0.467487
150	Ethiopia	0.444233
65	Malawi	0.432376
66	Mozambique	0.425232
49	Benin	0.416712
158	Trinidad and Tobago	0.410439
145	Saudi Arabia	0.395495
15	Haiti	0.385095
95	Tajikistan	0.366060
54	Ghana	0.327274
11	Somalia	0.318666
5	Uzbekistan	0.262195
124	New Zealand	0.243885
14	Chad	0.240146
12	Kenya	0.235216
10	Dem. Rep. Congo	0.232890
58	Sierra Leone	0.227155
159	S. Sudan	0.222629
68	Angola	0.211530
94	Afghanistan	0.161173
55	Guinea	0.153055
125	Australia	0.103304
53	Togo	0.087884
60	Central African Rep.	0.035555
83	Cambodia	0.012342
127	China	0.005728
144	Yemen	0.003567
86	Vietnam	0.002080
52	Cameroon	0.000000
6	Papua New Guinea	0.000000
157	Kosovo	0.000000
13	Sudan	0.000000
16	Dominican Rep.	0.000000
20	Timor-Leste	0.000000
31	Nicaragua	0.000000
32	Honduras	0.000000
50	Niger	0.000000
1	Tanzania	0.000000
73	Gambia	0.000000
85	Laos	0.000000
56	Guinea-Bissau	0.000000
57	Liberia	0.000000
84	Thailand	0.000000
61	Congo	0.000000
82	Vanuatu	0.000000
69	Burundi	0.000000
72	Madagascar	0.000000
0	Fiji	0.000000

	country	new_cases
3	United States of America	229042
25	Brazil	55649
130	United Kingdom	50239
111	Germany	49044
39	France	26514
17	Russia	26095
89	India	21822
21	South Africa	17710
122	Spain	16716
140	Czechia	16420
128	Italy	16202
114	Turkey	15692
103	Poland	12780
23	Mexico	12406
8	Argentina	11765
28	Colombia	11639
120	Netherlands	9533
100	Sweden	8846
2	Canada	8459
102	Ukraine	8404
7	Indonesia	8002
97	Iran	6272
121	Portugal	6049
117	Switzerland	5424
107	Romania	4875
29	Panama	4465
70	Israel	4186
108	Lithuania	3934
142	Japan	3856
155	Serbia	3236
139	Slovakia	3041
9	Chile	2964
71	Lebanon	2878
119	Belgium	2831
129	Denmark	2788
104	Austria	2550
93	Pakistan	2475
137	Slovenia	2435
74	Tunisia	2414
147	Morocco	2143
105	Hungary	1972
101	Belarus	1957
135	Malaysia	1870
116	Croatia	1850
133	Georgia	1738
112	Bulgaria	1729
77	United Arab Emirates	1723
123	Ireland	1718
76	Jordan	1674
27	Peru	1588
26	Bolivia	1485
148	Egypt	1411
109	Latvia	1367
30	Costa Rica	1315
90	Bangladesh	1235
40	Ecuador	1186
132	Azerbaijan	1052
51	Nigeria	1016
134	Philippines	1006
106	Moldova	990
110	Estonia	973
87	South Korea	967
113	Greece	942
80	Iraq	901
4	Kazakhstan	888
34	Guatemala	879
143	Paraguay	822
19	Norway	732
146	Cyprus	704
44	Botswana	675
126	Sri Lanka	646
149	Libya	585
99	Armenia	582
115	Albania	581
33	El Salvador	545
154	Bosnia and Herz.	531
24	Uruguay	518
92	Nepal	511
45	Namibia	482
150	Ethiopia	468
138	Finland	438
152	Uganda	396
156	Montenegro	378
118	Luxembourg	327
75	Algeria	323
43	Zimbabwe	300
64	Zambia	285
36	Venezuela	260
47	Mali	233
67	eSwatini	212
79	Kuwait	205
48	Mauritania	202
10	Dem. Rep. Congo	194
78	Qatar	193
96	Kyrgyzstan	189
46	Senegal	139
153	Rwanda	122
145	Saudi Arabia	113
66	Mozambique	113
12	Kenya	112
98	Syria	101
59	Burkina Faso	94
54	Ghana	90
22	Lesotho	89
42	Cuba	86
81	Oman	86
38	Suriname	83
65	Malawi	83
127	China	79
5	Uzbekistan	78
68	Angola	62
62	Gabon	61
35	Belize	56
94	Afghanistan	55
49	Benin	46
15	Haiti	41
41	Jamaica	41
141	Eritrea	32
95	Tajikistan	31
159	S. Sudan	29
14	Chad	29
11	Somalia	24
125	Australia	24
88	Mongolia	20
91	Bhutan	19
55	Guinea	19
131	Iceland	18
37	Guyana	18
63	Eq. Guinea	16
58	Sierra Leone	14
124	New Zealand	11
151	Djibouti	11
18	Bahamas	11
53	Togo	7
136	Brunei	5
158	Trinidad and Tobago	5
60	Central African Rep.	2
83	Cambodia	2
86	Vietnam	2
144	Yemen	1
31	Nicaragua	0
20	Timor-Leste	0
6	Papua New Guinea	0
32	Honduras	0
157	Kosovo	0
13	Sudan	0
16	Dominican Rep.	0
56	Guinea-Bissau	0
50	Niger	0
52	Cameroon	0
57	Liberia	0
61	Congo	0
69	Burundi	0
72	Madagascar	0
73	Gambia	0
1	Tanzania	0
82	Vanuatu	0
84	Thailand	0
85	Laos	0
0	Fiji	0

	country	new_fatalities
3	United States of America	3744
25	Brazil	1194
23	Mexico	1052
130	United Kingdom	982
111	Germany	963
17	Russia	585
128	Italy	575
103	Poland	565
21	South Africa	465
39	France	304
89	India	299
28	Colombia	289
102	Ukraine	257
114	Turkey	254
122	Spain	247
100	Sweden	243
7	Indonesia	241
97	Iran	149
8	Argentina	145
105	Hungary	137
140	Czechia	127
107	Romania	127
120	Netherlands	112
2	Canada	111
112	Bulgaria	110
117	Switzerland	101
104	Austria	90
139	Slovakia	82
119	Belgium	80
121	Portugal	79
108	Lithuania	75
134	Philippines	68
116	Croatia	65
113	Greece	58
93	Pakistan	58
148	Egypt	56
74	Tunisia	50
27	Peru	49
142	Japan	47
155	Serbia	44
29	Panama	42
147	Morocco	41
133	Georgia	38
132	Azerbaijan	34
137	Slovenia	34
129	Denmark	30
154	Bosnia and Herz.	26
71	Lebanon	26
106	Moldova	26
109	Latvia	23
143	Paraguay	22
34	Guatemala	22
90	Bangladesh	22
40	Ecuador	22
87	South Korea	21
70	Israel	15
149	Libya	15
30	Costa Rica	15
26	Bolivia	14
76	Jordan	14
33	El Salvador	14
123	Ireland	13
9	Chile	11
51	Nigeria	11
99	Armenia	10
145	Saudi Arabia	10
101	Belarus	10
67	eSwatini	9
98	Syria	8
80	Iraq	8
46	Senegal	7
92	Nepal	7
47	Mali	7
153	Rwanda	7
24	Uruguay	6
138	Finland	6
75	Algeria	6
135	Malaysia	6
118	Luxembourg	6
150	Ethiopia	5
110	Estonia	5
48	Mauritania	5
126	Sri Lanka	4
127	China	4
36	Venezuela	4
41	Jamaica	4
115	Albania	4
156	Montenegro	4
66	Mozambique	3
19	Norway	3
77	United Arab Emirates	3
11	Somalia	3
42	Cuba	2
12	Kenya	2
68	Angola	2
94	Afghanistan	2
59	Burkina Faso	2
146	Cyprus	2
152	Uganda	1
4	Kazakhstan	1
5	Uzbekistan	1
158	Trinidad and Tobago	1
65	Malawi	1
64	Zambia	1
79	Kuwait	1
43	Zimbabwe	1
96	Kyrgyzstan	1
35	Belize	1
45	Namibia	1
38	Suriname	1
124	New Zealand	0
151	Djibouti	0
136	Brunei	0
141	Eritrea	0
144	Yemen	0
157	Kosovo	0
131	Iceland	0
125	Australia	0
0	Fiji	0
95	Tajikistan	0
55	Guinea	0
53	Togo	0
52	Cameroon	0
50	Niger	0
49	Benin	0
44	Botswana	0
37	Guyana	0
32	Honduras	0
31	Nicaragua	0
22	Lesotho	0
20	Timor-Leste	0
18	Bahamas	0
16	Dominican Rep.	0
15	Haiti	0
14	Chad	0
13	Sudan	0
10	Dem. Rep. Congo	0
6	Papua New Guinea	0
54	Ghana	0
56	Guinea-Bissau	0
91	Bhutan	0
57	Liberia	0
88	Mongolia	0
86	Vietnam	0
85	Laos	0
84	Thailand	0
83	Cambodia	0
82	Vanuatu	0
81	Oman	0
1	Tanzania	0
78	Qatar	0
73	Gambia	0
72	Madagascar	0
69	Burundi	0
63	Eq. Guinea	0
62	Gabon	0
61	Congo	0
60	Central African Rep.	0
58	Sierra Leone	0
159	S. Sudan	0

	country	lethality
144	Yemen	29.089175
23	Mexico	8.833291
40	Ecuador	6.629884
13	Sudan	6.296106
98	Syria	6.205924
26	Bolivia	5.776905
148	Egypt	5.544334
14	Chad	5.007222
127	China	4.986649
57	Liberia	4.665542
97	Iran	4.520604
94	Afghanistan	4.242778
1	Tanzania	4.125737
0	Fiji	4.081633
47	Mali	3.827002
112	Bulgaria	3.734718
27	Peru	3.718372
154	Bosnia and Herz.	3.649142
128	Italy	3.532389
34	Guatemala	3.501597
113	Greece	3.471628
74	Tunisia	3.366954
10	Dem. Rep. Congo	3.360958
73	Gambia	3.265736
125	Australia	3.200141
50	Niger	3.179551
119	Belgium	3.017655
7	Indonesia	2.985075
130	United Kingdom	2.977499
105	Hungary	2.950777
58	Sierra Leone	2.942315
65	Malawi	2.920723
33	El Salvador	2.887293
75	Algeria	2.770086
11	Somalia	2.757743
31	Nicaragua	2.729077
9	Chile	2.718346
21	South Africa	2.697657
2	Canada	2.684724
8	Argentina	2.674407
122	Spain	2.653571
43	Zimbabwe	2.642202
28	Colombia	2.638182
157	Kosovo	2.602632
37	Guyana	2.595347
32	Honduras	2.572946
25	Brazil	2.544558
107	Romania	2.483673
123	Ireland	2.469026
39	France	2.427281
86	Vietnam	2.403846
48	Mauritania	2.388838
41	Jamaica	2.360666
15	Haiti	2.360236
68	Angola	2.323180
35	Belize	2.256621
137	Slovenia	2.225656
103	Poland	2.186569
18	Bahamas	2.163676
80	Iraq	2.154626
46	Senegal	2.121932
93	Pakistan	2.106459
143	Paraguay	2.096150
106	Moldova	2.057828
115	Albania	2.033710
67	eSwatini	2.011808
100	Sweden	1.995295
38	Suriname	1.957612
134	Philippines	1.953307
136	Brunei	1.910828
111	Germany	1.908505
64	Zambia	1.886424
53	Togo	1.883135
116	Croatia	1.851799
56	Guinea-Bissau	1.835237
17	Russia	1.796506
159	S. Sudan	1.779661
102	Ukraine	1.769742
99	Armenia	1.766764
158	Trinidad and Tobago	1.766685
3	United States of America	1.734062
12	Kenya	1.731930
104	Austria	1.718068
145	Saudi Arabia	1.713729
52	Cameroon	1.704913
117	Switzerland	1.695449
121	Portugal	1.682055
147	Morocco	1.681789
96	Kyrgyzstan	1.674851
22	Lesotho	1.648352
29	Panama	1.637528
63	Eq. Guinea	1.633739
140	Czechia	1.628940
109	Latvia	1.603360
138	Finland	1.550561
61	Congo	1.548929
150	Ethiopia	1.548573
87	South Korea	1.481725
51	Nigeria	1.476160
72	Madagascar	1.473411
90	Bangladesh	1.469475
149	Libya	1.459949
89	India	1.448746
120	Netherlands	1.429641
156	Montenegro	1.425223
142	Japan	1.402251
4	Kazakhstan	1.377449
49	Benin	1.353430
76	Jordan	1.301750
30	Costa Rica	1.291386
60	Central African Rep.	1.269394
59	Burkina Faso	1.266777
42	Cuba	1.240695
132	Azerbaijan	1.198791
139	Slovakia	1.192071
81	Oman	1.162998
124	New Zealand	1.156337
6	Papua New Guinea	1.153846
133	Georgia	1.098308
118	Luxembourg	1.066466
151	Djibouti	1.047390
153	Rwanda	1.042424
108	Lithuania	1.028802
155	Serbia	0.944204
24	Uruguay	0.941558
114	Turkey	0.940722
84	Thailand	0.911809
36	Venezuela	0.906109
66	Mozambique	0.892616
19	Norway	0.889614
45	Namibia	0.840012
110	Estonia	0.829175
71	Lebanon	0.817996
5	Uzbekistan	0.797558
70	Israel	0.793837
129	Denmark	0.775970
101	Belarus	0.735076
152	Uganda	0.723823
92	Nepal	0.710223
95	Tajikistan	0.676895
62	Gabon	0.668687
79	Kuwait	0.620767
54	Ghana	0.611638
55	Guinea	0.583643
146	Cyprus	0.540442
131	Iceland	0.503997
126	Sri Lanka	0.466020
135	Malaysia	0.419061
77	United Arab Emirates	0.322671
44	Botswana	0.272109
69	Burundi	0.247219
78	Qatar	0.170588
88	Mongolia	0.082305
141	Eritrea	0.079872
16	Dominican Rep.	0.000000
91	Bhutan	0.000000
20	Timor-Leste	0.000000
82	Vanuatu	0.000000
83	Cambodia	0.000000
85	Laos	0.000000